Name
Title | ||
|---|---|---|
A Coarse-to-Fine Deformable Transformation Framework for Unsupervised Multi-Contrast MR Image Registration with Dual Consistency Constraint |
Abstract | ||
|---|---|---|
Multi-contrast magnetic resonance (MR) image registration is useful in the clinic to achieve fast and accurate imaging-based disease diagnosis and treatment planning. Nevertheless, the efficiency and performance of the existing registration algorithms can still be improved. In this paper, we propose a novel unsupervised learning-based framework to achieve accurate and efficient multi-contrast MR i... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TMI.2021.3059282 | IEEE Transactions on Medical Imaging |
Keywords | DocType | Volume |
Image registration,Optimization,Biomedical imaging,Strain,Task analysis,Lesions,Transforms | Journal | 40 |
Issue | ISSN | Citations |
10 | 0278-0062 | 0 |
PageRank | References | Authors |
0.34 | 0 | 8 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weijian Huang | 1 | 2 | 1.05 |
| Hao Yang | 2 | 3 | 1.40 |
| Xinfeng Liu | 3 | 0 | 1.35 |
| Cheng Li | 4 | 4 | 3.10 |
| Ian Zhang | 5 | 0 | 0.34 |
| Rongpin Wang | 6 | 1 | 3.05 |
| Hairong Zheng | 7 | 56 | 28.24 |
| Shanshan Wang | 8 | 0 | 0.34 |